most citedA framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks

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cs.CE2024★ 5 cited

A review on data-driven constitutive laws for solids

Jan Niklas Fuhg, Govinda Anantha Padmanabha, Nikolaos Bouklas +6

This review article highlights state-of-the-art data-driven techniques to discover, encode, surrogate, or emulate constitutive laws that describe the path-independent and path-depe…

cs.CE2021

Local approximate Gaussian process regression for data-driven constitutive laws: Development and comparison with neural networks

Jan Niklas Fuhg, Michele Marino, Nikolaos Bouklas

Hierarchical computational methods for multiscale mechanics such as the FE and FE-FFT methods are generally accompanied by high computational costs. Data-driven approaches are…